Header Leaderboard Ad


Help in understanding the Demultiplexing summary files



No announcement yet.
  • Filter
  • Time
  • Show
Clear All
new posts

  • Help in understanding the Demultiplexing summary files

    Hi all,
    I'm working on analysing my RNA-seq data from NextSeq 550 machine.

    Among all the things I'm trying to understand, there is a main concern that I haven't found any information on.
    When I open my fastq files (per sample-index), I can see that each read has assigned the appropriate index in most of the cases, but also some of them have similar but not exact the exact index assigned (not the index belonging to a different sample, but different), and some have completely random indexes that have no similarity to the index that should be there. Is this a problem? I have already checked that the indexes I introduced in the sample sheet are correct.

    Moreover, when looking into the demultiplexing summary, I can see that my indexes are top in the most popular indexes, but then there are a bunch of random indexes that do not match to the indexes available in my RNA library preparation kit.

    And finally, is this related anyhow to how many undetermined reads I got? Around 20-25% for each lane. I added 1% PhiX control library to my sequencing.

    Thanks a lot!!

Latest Articles


  • seqadmin
    A Brief Overview and Common Challenges in Single-cell Sequencing Analysis
    by seqadmin

    ​​​​​​The introduction of single-cell sequencing has advanced the ability to study cell-to-cell heterogeneity. Its use has improved our understanding of somatic mutations1, cell lineages2, cellular diversity and regulation3, and development in multicellular organisms4. Single-cell sequencing encompasses hundreds of techniques with different approaches to studying the genomes, transcriptomes, epigenomes, and other omics of individual cells. The analysis of single-cell sequencing data i...

    01-24-2023, 01:19 PM
  • seqadmin
    Introduction to Single-Cell Sequencing
    by seqadmin
    Single-cell sequencing is a technique used to investigate the genome, transcriptome, epigenome, and other omics of individual cells using high-throughput sequencing. This technology has provided many scientific breakthroughs and continues to be applied across many fields, including microbiology, oncology, immunology, neurobiology, precision medicine, and stem cell research.

    The advancement of single-cell sequencing began in 2009 when Tang et al. investigated the single-cell transcriptomes
    01-09-2023, 03:10 PM